samvit_base_patch16.sa1b
Built by timm, samvit_base_patch16.sa1b is a 1 billion parameter image-generation model. samvit_base_patch16.sa1b is an open-weights image model with roughly 1 billion parameters.
by timm · 1B parameters
Best for
Ways to use samvit_base_patch16.sa1b in osFoundry
Connect with your own key (BYOK)
Open the key dialog and paste your timm API key. osFoundry discovers samvit_base_patch16.sa1b automatically — assign it to a Maestro role (router, direct, orchestrator, or fallback) in the Pipeline tab and it is live in every chat. Your key, your provider account — no token markup.
Deploy a dedicated endpoint
samvit_base_patch16.sa1b is open-weights — run it locally for free, or deploy a dedicated GPU endpoint in your workspace for reserved capacity with no rate limits.
Use it in a Room App
Room Apps declare AI features in their manifest, then call them with invokeAI:
import { invokeAI } from '@osfoundry/app-sdk'
// 'summarize' is an AI feature declared in your app manifest.
const result = await invokeAI('summarize', userText)
Call it from your own apps
Once a model is wired into your workspace you can host it as an API and reach it from your own services, scripts, or CI — outside osFoundry.
What hardware can run samvit_base_patch16.sa1b
samvit_base_patch16.sa1b runs on a single 16GB consumer GPU (~1 GB VRAM with KV-cache headroom). Full-precision inference fits on a single H100 80GB at FP16 precision (~3 GB).
samvit_base_patch16.sa1b vs similar models
Licence
Unspecified — Licence terms not specified — verify the upstream model card before commercial use.
Check upstream documentation.
Frequently asked about samvit_base_patch16.sa1b
Is samvit_base_patch16.sa1b free to use?
samvit_base_patch16.sa1b is free to run locally on your own hardware. Hosted access through osFoundry is metered (input Free (local), output Free (local)). You can switch between local and hosted at any time.
Can I use samvit_base_patch16.sa1b commercially?
Commercial use is allowed with conditions. Licence terms not specified — verify the upstream model card before commercial use. Check upstream documentation.
How much VRAM does samvit_base_patch16.sa1b need?
Approximately 1 GB at Q4 quantisation, or 3 GB at full FP16 precision. Fits on a single 24GB consumer GPU.
Can I run samvit_base_patch16.sa1b locally?
Yes. samvit_base_patch16.sa1b is open-weights and runs locally on a workstation GPU. osFoundry's local runtime handles model loading, quantisation, and routing.
What is samvit_base_patch16.sa1b best at?
samvit_base_patch16.sa1b is well-suited to image feature extraction.
How do I use samvit_base_patch16.sa1b in osFoundry?
Paste your timm API key in the key dialog (or deploy the open weights for self-hostable models), assign samvit_base_patch16.sa1b to a Maestro role in the Pipeline tab, then use it in chat, Room Apps via invokeAI, or your own apps.
Published by timm on May 18, 2023. Source: https://huggingface.co/timm/samvit_base_patch16.sa1b